While user operating a digital camera to take pictures, the problem of blurred images due to vibrations in hand has been beleaguering numerous photographers all the time. Generally speaking, when holding a conventional digital camera by a user in hand for photographic operations, before a picture is taken, the lens may be swung or moved because of accidental carelessness or incorrect gesture in holding the digital camera. Additionally, as the size for the digital camera becomes slimmer, the occurrence of blurred images caused by hand shakes when pressing down the shutter button on a compact digital camera also gets more commonly seen. Consequently, hand shakes could adversely influence the quality of taken pictures to a certain extent; for minor cases, the scene angle in the picture may slant or deviate; under more serious condition, the entire image can be blurred and obscured.
Several traditional anti-shake approaches have been developed and comprehensively applied to address to such an issue, including: (1) elevation of sensitivity in the photo-sensor (e.g., Charge-Coupled Device, CCD or Complementary Metal-Oxide-Semiconductor, CMOS) so as to reduce the required exposure time thereby curtailing the possibility in occurrence of blurred images. (2) application of optical anti-shake technique to move in real-time the lens or sensor in order to compensate for the offset in optical axis generated by hand shakes. Each of the aforementioned approaches has respective advantages and drawbacks, but with regards to current consumption trend, the first solution gets more widely implemented; however, since a picture is taken through increased sensitivity, an image of high noise is very likely generated. Therefore, a technology of multi-exposure image integration has been applied in recent years for reduction of noise in output images.
So far, the application of multi-exposure method for reducing high noises needs to first capture a series of images at high sensitivity regarding to a specific scene, and select a reference image among them, and perform geometric movement estimations on the rest captured images based on the selected reference image thereby finding the geometric conversion parameters between the other images and the reference image. Each of the other images are converted in accordance with the estimated motion parameters so that each image can be integrated in a point-to-point fashion with the selected reference image, and some integration techniques are used to integrate relevant image points distributed across such images into an image of low noises.
However, by applying this method, effective integration of high quality image may not be successfully achieved due to erroneous estimations of geometric conversion parameters in certain images and much noise in each input image, thus resulting in images of even worse quality. Also, at present, this method essentially uses the same exposure approach to acquire each image: for example, first determining an exposure time for a certain scene, and then applying the minimum secure shutter time to equivalently decide the number of images to take; whereas, more images it captures, the longer time the system needs for required processes, thus less reliable in the quality of output images after integration. As such, regarding to the aforementioned issues, it now becomes an urgent subject for the market applications in terms of demand to design an image capturing device and an exposure time adjusting method thereof which can effectively increase the image quality.